The rapidly increasing integration of renewable energy sources (RES) and electric vehicles (EVs) is making energy systems more sustainable. But it also causes unpredictable fluctuations and price volatility in energy markets. These findings address major concerns about the system's stability and efficiency. The conventional techniques of price forecasts cannot be relied upon in the face of fluctuating production and demand uncertainties. In all of the above circumstances, the use of Artificial Intelligence (AI) and digitalization techniques is quite effective in enhancing the stability of energy price forecasts. The use of digitalization techniques, such as Artificial Intelligence (AI)-based price forecast algorithms, digital twins, energy markets using blockchain trading, AI algorithms and data analysis of energy price volatility, and Vehicle to Grid (V2G) and price stability, is discussed in detail. The available literature has been studied, and it has been found that there is a need to focus on specific areas of energy markets and specific technologies. In all of the above circumstances, there is a need for an overall system-wide approach. In addition, further research is required on the compatibility of AI algorithms and performance review system requirements, transparency of decision support system software, and regulatory system requirements. In all of the above circumstances, the sustainability of energy price forecasts has been analyzed in detail. In addition, the use of multi-scenario-based sustainability has been discussed. The objective of the study is not only to enhance the sustainability of energy price forecasts, but also the adaptability of energy markets.

The rapid expansion of urban areas worldwide has intensified the pressure on energy systems, placing cities at the center of the global transition toward sustainability and climate neutrality [...]

Intelligent energy management systems are increasingly necessary for integrating renewable energy sources within microgrids. This paper investigates the application of a reinforcement learning (RL) neural network to optimize the operation of an electrochemical storage system in an environment composed of residential loads, commercial loads, and a photovoltaic plant, all connected to the grid. A dataset combining market purchase prices, photovoltaic generation, and residential and commercial load profiles was generated and used to train a Twin Delayed Deep Deterministic Policy Gradient (TD3) agent with the primary goal of deriving a reliable and adaptive post-training policy capable of maximizing photovoltaic self-consumption, minimizing operational costs through intelligent price arbitrage, and ensuring strict compliance with battery physical constraints. The system state includes battery state of charge, load demand, PV generation, and normalized market purchase prices, whereas the action represents the battery’s charge/discharge power, which is restricted from exporting energy to the grid. Results show that the agent learns to effectively store surplus PV energy and minimize grid dependency through dynamic charge management. The proposed approach outperforms strategies based solely on storing surplus self-generated energy and maintains the battery within safe operational limits. Tests with previously unseen data demonstrate robust, adaptive, and economically efficient energy management, highlighting the potential of reinforcement learning in intelligent energy systems.

Sustainable energy communities (ECs) are rapidly expanding in scale and heterogeneity, making fully centralized energy management increasingly impractical due to computational burden and privacy concerns. In this context, this review synthesizes distributed optimization (DO) as a practical management paradigm for ECs, identifies key application areas (demand response, distributed generation and storage management, and microgrid or smart-grid integration) and profiles scalability, privacy, and resilience characteristics. The survey follows a systematic protocol: records are sourced from Scopus, filtered with iteratively refined keyword sets, and screened following a PRISMA flow. Key technological enablers, such as blockchain/distributed ledgers, artificial intelligence, and game-theoretic constructs, are assessed and analyzed for how they support secure data exchange, real-time coordination, and incentive compatibility across multi-agent energy networks. The analysis highlights persistent challenges for DO at EC scale, including convergence under heterogeneity, time-varying conditions, communication delays, cybersecurity and privacy guarantees, while recent advances (e.g., ADMM) partially mitigate these issues without sacrificing local autonomy. Across representative studies, DO achieves near-centralized optimality with 0.0029% gap. Overall, we present an integrative framework that maps DO families to EC use cases and outlines research directions toward robust, privacy-preserving, and scalable EC optimization.

Battery Energy Storage Systems (BESS) are increasingly regarded as essential elements of the energy transition, ensuring stability and flexibility within the Na tional Power System. Their integration supports renewable energy absorption, mitigates generation-demand imbalances, and enhances overall energy security. This paper examines the energy and environmental performance of three storage configurations applied to a model micro-community consisting of an industrial consumer and a 200 kW photovoltaic plant. The analysis assesses their potential to optimize energy use, maximize self-consumption, and reduce CO emissions. Results highlight the differing contributions of each configuration to renewable integration and local energy efficiency.

The recent developments in our society have further proved the potential of the renewable energy communities (REC) to be a tool that enables easier transition towards a net-zero carbon economy. Their flexibility allows them to integrate different energy assets, such as storage and energy production, both in the rural and urban areas while at the same time improving the local grid. The battery energy storage system (BESS) represents an essential part of the community that allows it to better use its available resources. This paper aims to analyze the impact of different member roles within the community and how different approaches to storage impact the performance of the community.

The transition toward a net-zero emissions economy is increasingly driven by the escalating impacts of climate change. Energy communities (ECs) can support this transition by reducing reliance on fossil fuel based upstream generation and by providing flexibility services. Electric vehicles (EVs) can further contribute to decarbonisation by operating as distributed battery storage for small-scale systems. This paper simulates, as realistically as possible, an energy community that uses EVs as a battery energy storage system (BESS) instead of a stationary storage system, with the objective of minimising energy costs under several operational scenarios.

This paper evaluates the performance of a fully electrified residential energy system, which integrates photovoltaic panels, a heat pump and an electric vehicle charging station in the energy transition process towards near zero energy consumption. The real case study from Romania analyzes consumption behavior in the heating variant with a gas boiler and the modernization phase that included a 12 kW heat pump, $8,47 \mathrm{kWp}$ photovoltaic system and electric vehicle charging station. The photovoltaic system produced 9700 kWh annually, covering 96,81% of the household electricity demand. The economic analysis shows that the photovoltaic system achieves net savings over the system lifetime of 50.575,25 €, while the combined photovoltaic-heat pump system generates net savings of 30.287,95 € over a period of 25 years. The results confirm that residential electrification supported by local renewable energy generation significantly reduces energy costs and emissions.

The integration of wind sources in areas where wind potential allows the installation of such sources can lead to the destabilization of the areas. In Romania the national targets assumed for the year 2030: 43.9% reduction of the emissions compared to the level of $2005; 30.7 \%$ share of energy from renewable sources in gross final energy consumption. Since 2010, WPPs (wind power plants) have been put into operation, especially in the southeastern area of Romania. This area is also characterized by the presence of a nuclear power plant and interconnection lines with Bulgaria and the Republic of Moldova. The article follows the technical challenges faced by the electrical grid in areas dominated by WPP.

Paper presents a technical and economic analysis of the implementation of renewable energy solutions in urban buildings by installing balcony photovoltaic systems. It has been calculated that if 25% of all urban homes in Romania had a balcony photovoltaic system, a total installed power of approximately 1,058 MW would result. The legislative, technical and economic challenges that may hinder the development of these balcony photovoltaic solutions in Europe are analyzed. Information is presented on the influence on urban architecture according to current scientific research. The case study analyzed members of a community that installed balcony photovoltaic systems and optimized the location to increase renewable energy production.

Battery Energy Storage Systems (BESS) are increasingly recognized as a fundamental component of the energy transition and play a vital role in maintaining a stable balance within the National Power System. They significantly contribute to the efficient integration of renewable energy sources, the mitigation of generation and consumption fluctuations, and the enhancement of energy security. Among the direct advantages of implementing BESS are the reduction of the risk of power supply interruptions, the improvement of grid resilience in the face of fluctuations or unforeseen events, and the overall optimization of system efficiency through better power flow management. This paper analyzes the energy and environmental impact of three distinct energy storage configurations integrated into a model energy micro-community, composed of an industrial consumer and a 200 kW photovoltaic power plant. The study evaluates the potential for energy consumption optimization and the contribution of each storage solution to CO emission reduction, maximization of self-consumption, and efficient exploitation of locally available renewable energy resources.

The Clean Energy package recognizes and offers a favorable regulatory framework for citizens and energy communities with renewable energy sources. However, various countries’ national regulations will be highly important for the successful development of energy communities in existing cities and surrounding areas. Energy communities represent a way in which citizens and local authorities can invest in clean energy sources and energy efficiency, with several benefits in addition to the financial ones, like strengthening the concept of community and individual contributions to reductions in the overall carbon footprint. In this paper, an overview of recent developments in financial incentives in energy communities, their organization, and typologies, as well as benefits shared among the participants, is performed. The overview reveals the potential of energy communities in contributing to the economic, energetic, and social development of cities towards sustainable and smart cities.

The paper highlights the complexity of multi-energy integration (electricity and heat) in a regional economic system, by using the vectors represented by green hydrogen, green certificates and methanization of captured carbon dioxide, for a local market mechanism. The scale of application can go down to residential areas of energy self-producers. Regional multi-energy systems take into account the use of fossil fuels (at least methane), along with biomass for the production of electricity alongside that from renewable sources. Current multi-energy systems include the use of the combustion concept for the fuel mixture formed by and (HCNG). Part of the methane can be represented by synthesis, formed by the chemical relationship with (Sabatier reaction). This way, an energy recovery is achieved in the form of a synthesis fuel for captured , eliminating storage problems. The paper also presents the technological differences between the methanization of pure carbon dioxide, compared to that found in the combustion gases discharged directly from energy installations, innovative solution proposed by the authors. General constructive-functional and economic aspects relating to the existing methanizers at the current technological stage are also presented. Zonal energy integration addresses any region producing energy from a set of sources, which is to become economic in an independent operation of state energy systems. Economic simulation and operation systems are very complex, with generally recognized operators mentioned in the paper.

In response to the growing challenges posed by the climate change and the growing population the transition towards renewable energy sources and their development becomes essential. The following paper explores a solution that involves two available tools, hydrogen-based energy system and energy communities. By making use of a wind power plant and a hydrogen generator and the necessary data acquisition equipment, we study their effects on an European village and how much they can benefit the local energy community (EC) paired with a BESS (Battery Energy Storage System). The results showcase how incorporating smart technologies, forecasting algorithms and a local SCADA can allow the members to generate revenue, to lower their energy bill and at the same time improve the upstream grid flexibility and reduce the reliance on fossil fuel generated energy.

In these article, we discusses the analysis of the profitability of investments in energy storage batteries, in the context of injection policies in the grid in Romania. The study compares the compensation and energy sale regimes for prosumers and producers depending on the installed capacity, thus showing the impact of market prices and tax regulations on the return of investment (ROI). The case study has three scenarios, each with specific formulas for calculating ROI depending on the price of the stored energy according to the tax regulations. The scenarios focus on an industrial consumer in the textile field, with a continuous activity (24/7), who owns a photovoltaic power plant of 277.56 kWp an DC and 220.98 kW an AC. The annual consumption is 61.18 MWh, predominantly at night. The payback period (ROI) takes into account the implementation of a 215 kWh solution based on different fiscal scenarios, thus confirming the economic viability of the investment and the significant contribution to the reduction of operating costs in the long term.

A Renewable Energy Community (REC) is a group of users, consumers, and prosumers who come together to produce and consume renewable energy in order to reduce the costs and consumption of non-renewable energy. Photovoltaic production, net of CO2 emissions related to the construction of the plant, is a clean energy source, ideal for REC, to produce energy to be shared among members, however, the variability of solar radiation still represents a major challenge in managing photovoltaic energy production. The aspect of energy production forecasting is increasingly a crucial aspect to limit imbalances in the electricity grid, optimize the operation of generation, load and storage resources. The approach we propose is effectively adapted to solar plants such as small-scale ones installed in condominiums. For the latter, it is possible to develop an initial forecasting model based on the technical characteristics of the plant (such as nominal power and panel orientation), which can then be refined using machine learning techniques and the use of historical generation data. Once trained, the best-performing models require relatively limited computational resources to generate accurate forecasts. A photovoltaic forecasting model for RECs must be accurate to allow optimal management of energy production and consumption within the community. These models predict photovoltaic daily output to ensure that the energy produced meets the needs of the community, minimizing losses and increasing efficiency. The study aims to develop integrated energy systems, optimizing the interaction between different energy sources (renewable and conventional) and energy vectors (electric and thermal) to maximize overall efficiency and improve the operational management of energy microgrids, thus accelerating the transition to a sustainable energy future.

The evolution of renewable sources at a global level has led to multiple challenges in terms of electricity grid management. In recent years, countries that are part of ENTSO-E have experienced incidents that led to the disconnection of large consumption areas. In order to adapt to these unpredictable generation systems, measures can be implemented on the command and control side, so that decisions can be taken as soon as possible after the occurrence of events and certain things can be automated. Installing devices that operate on the grid forming (GFM) principle is a way to improve the operating parameters of the electric power system.

In response to the growing problem posed by the climate change, the necessity to find new ways to produce more energy pushes us to search or improve the tools required to transition towards a lower carbon emission economy. At the same time the recent advancements in digital technologies allow more control than ever in the interconnected systems of the local energy grid with the addition of smart meters and Internet of Things (IoT) devices. This paper aims to research and simulate an energy community that optimizes the energy consumption of each household member using Internet of Things for better data acquisition in order to improve the management of its energy resources and obtain the maximum financial benefit.

As a response to the ever growing need for energy and the effects caused by pollution, humanity is faced with the need to adapt. By using the existent technologies and applying them in an intelligent manner these problems can be mitigated, and in time solved. A tool that can help in reducing the dependency on fossil fuel is represented by Energy Communities. While their impact as an individual community might be small, by having a number of them distributed around the country, an improvement both to the quality of life for the members and for the upstream grid can be seen. By combining this concept with the control and flexibility over the energy system provided by a microgrid, a small scale and self-reliant energy system can be created and further improved with the use electric vehicles.

The article provides a comprehensive analysis of the development of electric vehicle charging infrastructure in Romania. The case study on the use of residential photovoltaic systems for charging electric vehicles demonstrates the profitability of the solution in various financing scenarios (including through the EFA program), as well as the significant potential for reducing costs and CO2 emissions. The comparative analysis between electric and conventional vehicles highlights the economic and environmental advantages of electric mobility, supporting the conclusion that the integration of renewable sources with charging infrastructure is a sustainable, scalable and essential solution for achieving European climate goals.